Journal of Cryptography and Network Security, Design and Codes

Cryptocurrency on the Blockchain: A New Era of Money and Trust

Yogita D. Sachdev — 2026-02-09

Cryptocurrency is a modern form of digital money that works through blockchain technology. It allows people to send and receive money safely without using banks or any middleman. This paper explains how blockchain supports cryptocurrencies by keeping records safe, clear, and unchangeable. It also describes how cryptocurrencies like Bitcoin, Ethereum, Ripple, Litecoin, and Stablecoins work and what makes each one different. The study discusses how cryptocurrency is changing the way people handle money. It offers faster transactions, lower costs, and accesses to financial services for people who do not have bank accounts. At the same time, it looks at the problems that still exist, such as changes in coin value, security risks, high energy use, and unclear government rules. These challenges make it difficult for cryptocurrencies to become a regular part of everyday life. The paper also looks at new ideas such as smart contracts, decentralized finance (DeFi), and digital tokens that can represent real-world assets like property or shares. These new uses show that cryptocurrency is not only a form of digital money but also a tool that can change how people make agreements and share value. Overall, this paper helps readers understand how cryptocurrencies work, what benefits they bring, what problems they face, and how they may shape the future of money. It aims to show that blockchain-based digital currencies can make finance more open, faster, and more secure if used responsibly.

Quantum-enhanced Federated Learning Framework for Large-scale Traffic Anomaly Detection

I. Kavya — 2026-03-23

The growing pace of development in smart transportation systems has raised new benchmarks for traffic information, introducing the need to ensure safety, efficiency, and security by devising complex anomaly detection systems. Privacy concerns, scale limitations, and computational constraints are among the significant limitations associated with the classical centralised approaches to machine learning. The suggested paper presents a novel theoretical framework that may be applied to integrate the ideas of quantum computing and federated learning systems to address the issue of detecting anomalies in the traffic data at large scales. The suggested quantum-enhanced federated learning (QEFL) system can attain geometric increases in the rate of pattern recognition, and the system does not violate the privacy of the data due to the decentralized learning and capabilities of quantum superposition and entanglement. Examine the theory behind quantum machine learning algorithms, examine federated learning protocols in traffic networks and propose a hybrid design to prepare quantum variational circuits using classical federated aggregation protocols. The model handles such critical questions as the reduction of the quantum noise, communication and heterogeneous data distribution among the traffic nodes. Theoretical analysis demonstrates that quantum advantage would be realized to make the detection of undetectable anomalies, such as cyberattacks, unusual traffic patterns, and infrastructure failures, simultaneously without violating the regulations of securing the data.

An AI-Enabled Tourist Safety and Incident Response Framework Using Geo-Fencing and Blockchain-based Digital Identity

Isha — 2026-04-07

Tourist safety has become a critical challenge due to the rapid growth of global travel and the increasing complexity of emergency response management. Traditional monitoring systems rely heavily on centralised infrastructures and reactive mechanisms, resulting in delayed incident detection and inefficient coordination. This paper proposes an AI-enabled Tourist Safety and Incident Response Framework that integrates geo-fencing, real-time data analytics, and blockchain-based digital identity management. The proposed system utilises IoT-enabled location tracking and cloud-based processing to monitor tourist movement patterns continuously. A machine learning-driven risk assessment module dynamically evaluates geospatial deviations and behavioural anomalies to generate real-time risk scores and automated alerts. Geo-fencing mechanisms define secure and restricted zones, enabling proactive detection of incidents. Additionally, a decentralised blockchain layer ensures secure identity verification, data integrity, and tamper-resistant record management. The layered architecture enhances system scalability, transparency, and operational efficiency while reducing response latency. Comparative analysis indicates that the proposed framework improves emergency coordination, resource allocation, and overall reliability compared to conventional centralised safety models. The framework contributes to the development of intelligent, secure, and responsive smart tourism infrastructures.

Quantum Computing and the Transformation of Modern Cyber Defense Mechanisms

Akshara Nitin Bhosale — 2026-04-08

Quantum computing constitutes a fundamental shift in computational science, with the potential to solve certain mathematical problems at speeds unattainable by classical machines. By utilising core quantum mechanical properties—such as superposition, entanglement, and interference—quantum systems challenge the computational assumptions that underpin modern public-key cryptography. Although advancements in quantum technology are expected to drive innovation in artificial intelligence, drug development, supply chain optimisation, and advanced materials research, they also pose significant risks to the security of global digital infrastructure. Widely used cryptographic protocols, including RSA, Elliptic Curve Cryptography (ECC), and Diffie–Hellman key exchange, rely on the presumed computational intractability of integer factorisation and discrete logarithm problems. However, Shor’s algorithm demonstrates that a sufficiently advanced quantum computer could solve these problems in polynomial time, effectively compromising the security of current public-key infrastructures. In parallel, Grover’s algorithm reduces the effective key strength of symmetric cryptographic systems, such as Advanced Encryption Standard (AES), by significantly accelerating brute-force search processes. This study provides an in-depth evaluation of cybersecurity risks introduced by quantum computing across public-key systems, symmetric encryption, and cryptographic hash functions. It reviews post-quantum cryptographic standards developed by the National Institute of Standards and Technology (NIST) and analyses the supporting role of Quantum key distribution (QKD), with particular attention to the BB84 protocol. A structured transition strategy is proposed, emphasising cryptographic agility, hybrid cryptographic implementations, infrastructure upgrades, and coordinated regulatory frameworks. The analysis confirms that quantum-related cybersecurity risks are grounded in mathematical proof rather than theoretical speculation. Postponing migration to quantum-resistant systems increases vulnerability across government institutions, financial networks, defense systems, and critical infrastructure. A proactive shift toward quantum-resilient cryptographic architectures is therefore essential to maintain confidentiality, integrity, and trust in digital systems over the coming decades.

BoreConnect: Streamlining Public URL Exposure via a Unified Web Interface for Bore CLI

Tejas Sadashiv Jondhale — 2026-04-08

Public URL exposure of local services is frequently required during rapid prototyping, remote debugging, and short-lived integration testing. Although tunnelling utilities such as Bore offer a lightweight mechanism for NAT traversal, their terminal-centric workflow introduces avoidable operational friction: manual command construction, repeated context switching between terminal and browser, and error-prone transcription of relay-assigned endpoints. This paper presents BoreConnect, a Spring Boot control plane that manages an unmodified Bore CLI instance as a supervised operating-system process and publishes the discovered public endpoint through a web interface and REST endpoints. BoreConnect continuously drains the CLI output stream to prevent blocking, extracts the relay-assigned port using regular-expression matching, and exposes the resulting public URL via a status API for near-real-time consumption by a browser client. A test structure takes shape through clear cause-and-effect measures, built around numbers that track how fast tunnels form, how often they work, mistakes by users, shifts between tasks, and system load. Variables are split into what changes and what responds, forming a backbone for checking real-world performance without guesswork creeping in. Metrics land firmly on timing, accuracy, repetition, effort gaps, and demand on tools. Each piece connects not just logically but through observable results piling up over trials.